1 Libreria simPop

2 Datos de la EPH

2.1 Tramos de edades

age=as.factor(c("0-4","5-9","10-14","15-19","20-24","25-29","30-34","35-39","40-44","45-49","50-54","55-59","60-64","65-69","77-74","75-79","80+"))
agex=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17)

2.2 Poblacion en cada tramo

pop=c(0,0,0,38254,31738,44179,56517,56386,69933,60672,57664,61748,46811,39420,23147,12631,5121)

x <-data.frame(age,agex,pop)
x
##      age agex   pop
## 1    0-4    1     0
## 2    5-9    2     0
## 3  10-14    3     0
## 4  15-19    4 38254
## 5  20-24    5 31738
## 6  25-29    6 44179
## 7  30-34    7 56517
## 8  35-39    8 56386
## 9  40-44    9 69933
## 10 45-49   10 60672
## 11 50-54   11 57664
## 12 55-59   12 61748
## 13 60-64   13 46811
## 14 65-69   14 39420
## 15 77-74   15 23147
## 16 75-79   16 12631
## 17   80+   17  5121

3 Resultados

s<-sprague(x[,3])

if (x[,2]>3) s<-sprague(x[,3]) else 0

result<-data.frame(s)
result
##              s
## 0   -1285.3344
## 1    -306.0320
## 2     306.0320
## 3     612.0640
## 4     673.2704
## 5     550.8576
## 6     306.0320
## 7       0.0000
## 8    -306.0320
## 9    -550.8576
## 10   -867.3152
## 11  -1388.2432
## 12  -1082.2112
## 13    500.0768
## 14   2837.6928
## 15   5062.3760
## 16   7470.1344
## 17   8948.1664
## 18   8894.0304
## 19   7879.2928
## 20   7047.4656
## 21   6133.2512
## 22   5666.1072
## 23   6012.9152
## 24   6878.2608
## 25   7580.0624
## 26   8230.9936
## 27   8879.4656
## 28   9473.5616
## 29  10014.9168
## 30  10598.9184
## 31  11256.6912
## 32  11649.6352
## 33  11634.7232
## 34  11377.0320
## 35  11126.2880
## 36  10762.4928
## 37  10766.9248
## 38  11381.8448
## 39  12348.4496
## 40  13212.1728
## 41  14119.7248
## 42  14588.5648
## 43  14350.5648
## 44  13661.9728
## 45  13048.5072
## 46  12406.6352
## 47  11903.7552
## 48  11676.6752
## 49  11636.4272
## 50  11515.4544
## 51  11317.1312
## 52  11303.5712
## 53  11562.3632
## 54  11965.4800
## 55  12339.8128
## 56  12770.9920
## 57  12838.9200
## 58  12333.2400
## 59  11465.0352
## 60  10629.4608
## 61   9715.9440
## 62   9026.6640
## 63   8741.7120
## 64   8697.2192
## 65   8572.6480
## 66   8460.2128
## 67   8153.8848
## 68   7527.9648
## 69   6705.2896
## 70   5929.9936
## 71   5147.9680
## 72   4472.0480
## 73   3981.3040
## 74   3615.6864
## 75   3231.6736
## 76   2852.6880
## 77   2502.1520
## 78   2175.6640
## 79   1868.8224
## 80+  5121.0000